Evaluation of Support Types of Volcanic Clastic Sand and Gravels Based on Electrical Imaging Logging - ZHAO Xiaoqing; WANG Xiangyu; ZHANG Zhiguo; ZHANG Weifeng; CHEN Haifeng (Cejing jishu)
The combined effect of river transport and volcanic action during the deposition of volcanic clastic sand conglomerate causes large variations in rock grain size and complex pore structure of different grain size combinations, which affects the reservoir quality. How to use logging date to evaluate rock grain size and the combination patterns of different grain sizes is an urgent problem to be solved in resevoir evaluation. The main mineral composition and parent rock type characteristics of the study area were obtained based on the whole-rock analysis experimental results of X diffraction. By observing core photos combined with petrographic experimental data, it is found that the volcanic clastic sand conglomerates in the study area commonly have a skeleton containing low-resistance conglomerates of acidic volcanic rocks and high-resistance conglomerates of normal deposition. Based on the micro-resistivity scanning imaging logging data, the watershed transformation algorithm was used to quantitatively calculate the content of high and low resistance gravels and to establish the lithological identification classification criteria in the study area. Based on the particle size spectrum generated by the sliding window method, an particle size area spectrum was constructed to quantitatively evaluate the content of different gravel grades to obtain the distribution characteristics of different gravel grades. By analyzing the oil-bearing characteristics of the core in relation to different grain-size combinations, the support type of gravel particles is determined, and the combination of the particle size spectrum and the particle size area spectrum results in an evaluation method of the support type of volcanic clastic sand conglomerate based on electrical imaging logging. The method makes full use of the advantages of electrical imaging logging data in gravel identification, and provides an important means to finely delineate the lithology identification and grain-size combination pattern evaluation of volcanic clastic sand conglomerates.